Paper presented at Strathmore International Math Research Conference on July 23 - 27, 2012Paper presented at Strathmore International Mathematics Research Conference on July 23 - 27, 201

Omollo, Raymond

English

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Definition and Analysis of Endpoints in Clinical Trials for Visceral Leishmaniasis:PhD UpgradeRaymond Omollo, BSc. MSc. (UoN)27 July 2012Presentation Outline• Background• Problem Statement• Objectives• Methodology• Conclusion Background • Visceral Leishmaniasis (VL) also known as kala-azar, is a vector-borne parasitic disease– Characterized by fever, substantial weight loss, swelling of the spleen and liver, and anemia • The diagnosis and assessment of cure in VL is primarily through internal tissues aspiration– Painful and Invasive • VL clinical trials generally take long to conclude– Patient recruitment – Evidence for complete cure made at least 6 months after treatment completionBackground cont…• Clinical Trials– Experiments conducted in humans to compare the effect and value of intervention(s)– The intervention could be a therapeutic agent, devise, diagnostic, regimens or procedures• End points– the clinical outcome time point which provides evidence sufficient to fully categorize clinically the effect of a treatment that would support a regulatory claim for that treatment– Its choice and timing is crucial to the success of any clinical trialBackground cont…• Safety Data– Include both adverse events and laboratory measurements– Collected as part of patient monitoring to detect any safety or efficacy problems• Group sequential designs like the triangular test (TT) have become useful in the conduct of phase II clinical trials– Also useful in the case of HIV-VL coinfection– Timely decision on whether a treatment is sufficiently effective to warrant further evaluation in phase III need to be madeProblem Statement• Involvement in the LEAP trials and discussions with the Investigators led to interest in the research questions and need to address them for future trials;– Diagnosis and assessment of VL final cure– Timing for final cure assessment in VL– Analysis of final cure following TT– Reporting & Analysis of safety data for VLObjectives • Develop a predictive model based on clinical signs & symptoms of VL in assessment of final cure as an alternative to parasitology • Estimate the optimal timing for final cure assessment post end of treatment in VL patients • Develop alternative analysis approach for final cure (secondary endpoint) following the TT design• Devise new methods for the design, analysis and reporting of secondary endpoint markers for VL Methodology • Multi-state models• Logistic regression• Analysis following TT• Repeated measures analysis• Survival AnalysisTiming for Final Cure• Look at the different event outcomes in VL after treatment administration– Cure, failure and relapse considered as transient states. – Death is also an event but for purposes of this analysis will be excluded as it is an absorbing state. • We will follow a Markov model with statistical model specification via transition intensities and likelihood inference as in Andersen et alFinal Cure Assessment• Tabulate signs and symptoms of VL by final cure status• Logistic regression to build a multivariate model• Prepare sensitivity, specificity, positive predictive value (PPV) & negative predictive value (NPV) tables based on this approach• Validate the algorithm proposed by Rahmenet al on the LEAP dataAnalysis following TT• Use LEAP 0208 data set to validate what is proposed by Omollo et al for final cure– Error rate and power• Simulate trial data sets under variable assumptions for parameters p0 & pa for both approaches. – Omollo et al & Liu et al• Estimate final cure, standard error and the confidence intervals.Markers for Efficacy • Use repeated measures analysis techniques based on the assumptions of normality, random selection and homogeneity of variance • Model the change during hospitalization for each parameter• Survival analysis techniques– Frailty models for competing risks if anyAnalyses Soft wares• STATA• R• Familiar with both soft wares• Strengthen statistical computing skills using bothConclusion • Overall– Improve knowledge and the application of statistical rigor in the methods for design and analysis of VL trials• Come up with a suitable model in the assessment of final cure in the absence of parasitology. • Estimate the optimal timing for final cure assessment post end of treatment in VL patientsConclusion cont…• A better understanding of the methodological issues in sequential designs particularly the TT in phase II trials; – Analysis of final cure in VL.• Improved methods for the design, analysis and reporting of secondary endpoint markers for VLAcknowledgement• Supervisor: – Prof. N. Omolo Ongati• Advisors: LSHTM– Neal Alexander, PhD– Tansy Edwards, MSc, MMath• DNDi– Employer & Sponsor– Data• LEAP– Data

Definition and analysis of endpoints in clinical trials for visceral leishmaniasis:

https://su-plus.strathmore.edu/bitstream/11071/3560/1/Definition%20and%20Analysis%20of%20Endpoints.pdf

Definition and analysis of endpoints in clinical trials for visceral leishmaniasis:

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